Designers of signal processing systems, e.g., imaging systems, often assess the performance of their designs in terms of physical parameters such as contrast, resolution and/or bit-rate efficiency in compression/decompression (codec) processes. While these parameters can be easily measured, they may not be accurate gauges for evaluating performance. The reason is that end users of imaging systems are generally more concerned with the subjective visual performance such as the visibility of artifacts or distortions and in some cases, the enhancement of these image features which may reveal information such as the existence of a tumor in an image, e.g., a MRI (Magnetic Resonance Imaging) image or a CAT (Computer-Assisted Tomography) scan image.
For example, an input image can be processed using two different codec algorithms to produce two different codec images. If the measure of codec image fidelity is based purely on parameters such as performing mean squared error (MSE) calculations on both codec images without considering the psychophysical properties of human vision, the codec image with a lower MSE value may actually contain more noticeable distortions than that of a codec image with a higher MSE value.
Therefore, a need exists in the art for a method and apparatus for assessing the effects of physical parameters on the subjective performance of a signal processing system, e.g., an imaging system. Specifically, a need exists for a method and apparatus for assessing the visibility of differences between two sequences of time-varying visual images.